code: def _constant_fill(
      g: jit_utils.GraphContext, sizes, dtype: int, const_value
  ):
      if dtype is None:
          scalar_type = _type_utils.JitScalarType.FLOAT
      else:
          scalar_type = _type_utils.JitScalarType(dtype)
      if not scalar_type.dtype().is_floating_point:
          result = g.op(
              "ConstantFill",
              sizes,
              dtype_i=_type_utils.JitScalarType.FLOAT.onnx_type(),
              input_as_shape_i=1,
              value_f=const_value,
          )
          return g.op("Cast", result, to_i=scalar_type.onnx_type())
      else:
          return g.op(
              "ConstantFill",
              sizes,
              dtype_i=scalar_type.onnx_type(),
              input_as_shape_i=1,
              value_f=const_value,
          )
  
imports: import functools
  import warnings
  import torch
  from torch._C import _onnx
  from torch.onnx import _type_utils, errors, symbolic_helper, symbolic_opset9
  from torch.onnx._internal import jit_utils, registration
label_desc: Use image node_id 15 for calling a global function with example usage: _constant_fill(g, sizes, dtype, const_value) and returns: g, g